A TWO-STAGE MATHEMATICAL PROGRAMMING MODEL FOR DISTRIBUTED PHOTOVOLTAIC PROJECT PORTFOLIO SELECTION WITH INCOMPLETE PREFERENCE INFORMATION

With the rapid growth of solar photovoltaic (PV) market, many distributed PV power projects are introduced to market. Selecting a rational project investment portfolio is complex and challenging task for energy enterprises as both financial non-financial factors needed be considered under limited information resources. This study presents two-stage hybrid multi-attribute decision-making integer programming model selection. In Stage I, multiple attribute group method based on mathematical used evaluate value incomplete preference information. Compensative weighted averaging operators with an adjustable parameter utilized capture subjective attitudinal character expert in aggregation process. Then, rank acceptability index developed measure each project’s support degree dimension. II, bi-objective constructed optimize portfolios, which considers values resource, carbon emission other strategic constraints. The applicability effectivity proposed approach demonstrated by case